Introduction

Project Purpose and Significance

Obesity continues to increase as a public health emergency, with the origins of most adult obesity being in childhood. Effective clinical approaches are urgently needed to prevent or reverse childhood obesity. The gut-associated microbiome is an established central factor in energy harvest, hepatic function, insulin sensitivity, and adipose tissue homeostasis, making it a critical target for obesity intervention strategies.

This project represents a collaborative effort between Lurie Children’s Hospital and Abbott Nutrition to investigate interpersonal variation in energetics and short-chain fatty acid (SCFA) production of obesity-associated gut microbiota in response to slow and fast digestible carbohydrates. The work builds upon foundational research demonstrating that carbohydrate quality, rather than quantity alone, plays a crucial role in metabolic health.

Scientific Foundation and Motivation

The project was motivated by compelling evidence from the Frontiers in Nutrition paper by Wang et al. (2022) that demonstrated the therapeutic potential of slowly digestible carbohydrates (SDC) in metabolic syndrome and obesity management. This seminal work showed that SDC displays beneficial effects on reducing glucose excursions in healthy, insulin-resistant, and type 2 diabetic individuals, inducing a slow and prolonged glucose release that results in reduced postprandial glycemic responses and extended glycemic index values.

In type 2 diabetic patients, SDC-rich diets (60g/day) reduced glycemic variability parameters by 17-23%, with these parameters correlating with HbA1c, suggesting potential for long-term glycemic improvement. The Frontiers paper also demonstrated that foods with the highest SDC content (23.9-27.5 g/100g) induce the lowest glycemic responses with the lowest incremental AUC of glucose and insulin concentration.

Comparative Evidence from Murine Models

In comparison to fast digestible carbohydrate (FDC) sources, the Abbott group has shown in murine models of obesity that nutrition with slow digestible carbohydrates (SDC) reverses obesity-associated phenotypes, including elevated body mass, insulin resistance, and systemic inflammation. However, the interpersonal differences in SDC responses by the childhood-associated human microbiota may not be fully predicted in murine obesity models.

Interpersonal Variation in Human Microbiota

Lurie investigators and colleagues have shown interpersonal variation in the production of short-chain fatty acids (SCFA) by the human gut microbiome from adolescents with obesity in response to ex vivo prebiotic exposure, suggesting that complex carbohydrate utilization by the microbiota varies between individuals and thus may affect who responds to SDC and other nutritional approaches to obesity.

Understanding the variation in the compositional and metabolic responses of the childhood-associated microbiota may inform future obesity-treatment trials and precision approaches to obesity therapy.

Project Objectives

The main objectives of this project are to:

  1. Measure variation in responses between different human gut-associated microbiome communities to FDC and SDC
  2. Identify childhood-associated organisms with facile utilization of SDC
  3. Test interindividual variation of short-chain fatty acid production among fecal microbiota samples to slow and fast digestible carbohydrates
  4. Measure energy harvest differences between human obesity-associated fecal microbiota
  5. Isolate SDC bacterial utilizers using single cell isolation techniques towards the future goal of creating obesity treatment synbiotic combinations

Clinical Impact

Understanding the interpersonal differences in SDC utilization by the childhood-associated human microbiota may inform future obesity-treatment trials through the identification of likely responders and, subsequently, precision approaches to obesity therapy. This precision nutrition approach could revolutionize childhood obesity treatment by enabling personalized dietary interventions based on individual microbiome composition and metabolic capacity.

Analysis Overview

This document presents the analysis of short-chain fatty acids (SCFAs) in the Abbott carbohydrate obesity project. The analysis examines how SCFA analytes change between experimental groups, carbohydrate types, and time points, with particular focus on identifying interpersonal variation in metabolic responses to different carbohydrate sources.

Methods

Metabolomics Overview

The fecal metabolome was analyzed using targeted metabolomics approaches. The DFI Host-Microbe Metabolomics Facility (DFI-HMMF) analyzed fecal material using validated methods and analysis pipelines. All compounds were validated through retention time and fragmentation comparison to standards and available databases.

SCFA Analysis using PFBBr Panel

Short chain fatty acids were analyzed using Gas chromatography-mass spectrometry (GC-MS) following derivatization with pentafluorobenzyl bromide (PFBBr). SCFAs (acetate, butyrate, propionate) were quantitatively analyzed following PFB derivatization and detection by negative collision induced gas chromatography-mass spectrometry ((-)-CI-GC-MS, Agilent 8890). Additional compounds including 5-aminovalerate and succinate were also quantified.

Detailed SCFA Analysis Protocol

The following section outlines the specific protocol used for SCFA derivatization and GC-MS analysis.

Short chain fatty acids were derivatized as described by Haak et al. with modifications. The metabolite extract (100 µL) was added to 100 µL of 100 mM borate buffer (pH 10), 400 µL of 100 mM pentafluorobenzyl bromide in Acetonitrile, and 400 µL of n-hexane in a capped mass spec autosampler vial. Samples were heated to 65°C for 1 hour while shaking at 1300 rpm. After cooling, samples were centrifuged at 4°C, 2000 x g for 5 min, allowing phase separation. The hexanes phase was transferred and analyzed.

Samples were analyzed using a GC-MS (Agilent 7890A GC system, Agilent 5975C MS detector) operating in negative chemical ionization mode, using a HP-5MSUI column (30 m x 0.25 mm, 0.25 µm), methane as the reagent gas and 1 µL split injection (1:10 split ratio). A 10-point calibration curve was prepared with acetate (100 mM), propionate (25 mM), butyrate (12.5 mM), and succinate (50 mM), with 9 subsequent 2x serial dilutions.

Sample Extraction

This section describes the procedure for extracting metabolites from the fecal samples prior to analysis.

Extraction solvent (80% methanol spiked with internal standards and stored at -80°C) was added at a ratio of 100 mg of material/mL of extraction solvent. Samples were homogenized at 4°C on a Bead Mill 24 Homogenizer, set at 1.6 m/s with 6 thirty-second cycles, 5 seconds off per cycle. Samples were then centrifuged at -10°C, 20,000 x g for 15 min and the supernatant was used for analysis.

Data Analysis

Load Metadata

Load SCFA Data

## Dataset dimensions: 440 16
## Sample groups: Case Control
## Carbohydrate types: Rapid Digestible Slow Digestible No Carbohydrate
## Time points: 0 48

Summary Statistics

## Total observations after averaging technical replicates: 480

SCFA Ratio Analysis

## SCFA ratio analysis completed. Total ratio observations: 376

SCFA Ratio Summary Statistics

This table provides summary statistics for the calculated SCFA ratios across all experimental conditions.

Summary Statistics for SCFA Ratios
Group Carbohydrate Type Time (Hours) Ratio Type n Mean Median SD SEM Q25 Q75
Case No Carbohydrate 0 acetate_butyrate_propionate_ratio 8 9.576 7.658 6.383 2.257 5.564 10.827
Case No Carbohydrate 0 acetate_butyrate_ratio 8 4.407 4.395 1.448 0.512 3.179 5.050
Case No Carbohydrate 0 acetate_propionate_ratio 8 7.615 6.569 4.683 1.656 4.478 8.970
Case No Carbohydrate 0 butyrate_propionate_ratio 8 1.961 1.283 1.774 0.627 0.996 1.857
Case No Carbohydrate 48 acetate_butyrate_propionate_ratio 8 6.579 5.847 2.538 0.897 4.819 7.974
Case No Carbohydrate 48 acetate_butyrate_ratio 8 5.315 5.395 0.940 0.332 4.772 6.081
Case No Carbohydrate 48 acetate_propionate_ratio 8 5.536 4.960 2.169 0.767 4.102 6.835
Case No Carbohydrate 48 butyrate_propionate_ratio 8 1.043 0.895 0.394 0.139 0.827 1.139
Case Rapid Digestible 0 acetate_butyrate_propionate_ratio 8 20.790 8.678 36.448 12.886 7.454 9.671
Case Rapid Digestible 0 acetate_butyrate_ratio 8 4.023 4.009 0.866 0.306 3.215 4.439
Case Rapid Digestible 0 acetate_propionate_ratio 8 16.054 7.004 27.446 9.704 6.238 7.584
Case Rapid Digestible 0 butyrate_propionate_ratio 8 4.736 1.601 9.008 3.185 1.217 2.151
Case Rapid Digestible 48 acetate_butyrate_propionate_ratio 8 10.099 10.078 3.954 1.398 7.287 13.481
Case Rapid Digestible 48 acetate_butyrate_ratio 8 6.137 5.618 3.219 1.138 3.280 8.919
Case Rapid Digestible 48 acetate_propionate_ratio 8 8.401 9.018 3.375 1.193 5.390 10.715
Case Rapid Digestible 48 butyrate_propionate_ratio 8 1.698 1.206 1.047 0.370 1.081 2.347
Case Slow Digestible 0 acetate_butyrate_propionate_ratio 8 11.006 8.438 9.220 3.260 6.853 9.767
Case Slow Digestible 0 acetate_butyrate_ratio 8 4.103 4.002 1.260 0.445 3.073 4.530
Case Slow Digestible 0 acetate_propionate_ratio 8 8.631 6.600 6.754 2.388 5.761 8.030
Case Slow Digestible 0 butyrate_propionate_ratio 8 2.375 1.667 2.546 0.900 1.092 1.906
Case Slow Digestible 48 acetate_butyrate_propionate_ratio 8 10.163 10.560 4.250 1.503 6.143 14.160
Case Slow Digestible 48 acetate_butyrate_ratio 8 5.299 4.548 2.071 0.732 4.267 5.495
Case Slow Digestible 48 acetate_propionate_ratio 8 8.503 8.388 3.797 1.343 4.998 12.464
Case Slow Digestible 48 butyrate_propionate_ratio 8 1.660 1.515 0.706 0.250 1.160 1.997
Control No Carbohydrate 0 acetate_butyrate_propionate_ratio 7 8.711 9.156 2.169 0.820 7.199 10.238
Control No Carbohydrate 0 acetate_butyrate_ratio 7 3.816 3.471 0.932 0.352 3.190 4.712
Control No Carbohydrate 0 acetate_propionate_ratio 7 6.847 6.889 1.768 0.668 5.775 7.886
Control No Carbohydrate 0 butyrate_propionate_ratio 7 1.864 1.643 0.626 0.237 1.424 2.096
Control No Carbohydrate 48 acetate_butyrate_propionate_ratio 8 6.282 5.134 2.395 0.847 4.934 7.064
Control No Carbohydrate 48 acetate_butyrate_ratio 8 5.378 5.102 1.161 0.411 4.835 5.950
Control No Carbohydrate 48 acetate_propionate_ratio 8 5.255 4.426 1.963 0.694 4.122 5.843
Control No Carbohydrate 48 butyrate_propionate_ratio 8 1.027 0.941 0.458 0.162 0.673 1.221
Control Rapid Digestible 0 acetate_butyrate_propionate_ratio 8 15.522 9.262 18.154 6.418 8.157 11.390
Control Rapid Digestible 0 acetate_butyrate_ratio 8 4.468 4.327 1.394 0.493 3.885 4.862
Control Rapid Digestible 0 acetate_propionate_ratio 8 12.891 7.761 16.022 5.665 6.287 8.831
Control Rapid Digestible 0 butyrate_propionate_ratio 8 2.631 1.890 2.215 0.783 1.304 2.458
Control Rapid Digestible 48 acetate_butyrate_propionate_ratio 8 11.973 12.460 3.871 1.369 8.610 14.422
Control Rapid Digestible 48 acetate_butyrate_ratio 8 5.286 4.328 2.499 0.884 3.550 7.198
Control Rapid Digestible 48 acetate_propionate_ratio 8 9.804 11.047 3.107 1.099 7.525 11.547
Control Rapid Digestible 48 butyrate_propionate_ratio 8 2.169 1.813 1.097 0.388 1.411 2.876
Control Slow Digestible 0 acetate_butyrate_propionate_ratio 7 8.904 9.176 2.205 0.833 7.054 10.061
Control Slow Digestible 0 acetate_butyrate_ratio 7 4.131 4.232 1.427 0.539 3.469 4.494
Control Slow Digestible 0 acetate_propionate_ratio 7 7.049 6.519 1.895 0.716 5.761 8.051
Control Slow Digestible 0 butyrate_propionate_ratio 7 1.855 1.376 0.727 0.275 1.336 2.251
Control Slow Digestible 48 acetate_butyrate_propionate_ratio 8 9.910 8.598 3.955 1.398 7.158 11.367
Control Slow Digestible 48 acetate_butyrate_ratio 8 4.178 3.964 1.273 0.450 3.187 5.269
Control Slow Digestible 48 acetate_propionate_ratio 8 7.943 7.105 3.354 1.186 5.952 8.938
Control Slow Digestible 48 butyrate_propionate_ratio 8 1.967 1.709 0.755 0.267 1.569 2.327

Statistical Analysis of SCFA Ratios

SCFA Ratio Group Comparisons

This table shows the results of t-tests comparing SCFA ratios between the control and case groups.

Group Comparisons of SCFA Ratios
Ratio Type .y. group1 group2 n1 n2 statistic df P-value Adjusted P-value Significance
acetate_butyrate_propionate_ratio ratio_value control case 46 48 -0.4272 71.8029 0.670 0.702 ns
acetate_butyrate_ratio ratio_value control case 46 48 -0.8740 90.2732 0.384 0.702 ns
acetate_propionate_ratio ratio_value control case 46 48 -0.3842 78.1780 0.702 0.702 ns
butyrate_propionate_ratio ratio_value control case 46 48 -0.5493 56.1671 0.585 0.702 ns

SCFA Ratio Carbohydrate Type Comparisons

This table shows the results of ANOVA tests examining the effect of different carbohydrate types on SCFA ratios.

ANOVA Results for Carbohydrate Type Effects on SCFA Ratios
Ratio Type Effect DFn DFd F P-value p<.05 ges Adjusted P-value Significance
acetate_butyrate_propionate_ratio carbohydrate_type 2 91 2.548 0.084 0.053 0.1680 ns
acetate_butyrate_ratio carbohydrate_type 2 91 0.765 0.468 0.017 0.4680 ns
acetate_propionate_ratio carbohydrate_type 2 91 2.726 0.071 0.057 0.1680 ns
butyrate_propionate_ratio carbohydrate_type 2 91 1.768 0.176 0.037 0.2347 ns

SCFA Ratio Post-hoc Carbohydrate Comparisons

Following the ANOVA, pairwise t-tests were performed to compare each carbohydrate type to the ‘no carbohydrate’ control for SCFA ratios.

Pairwise Comparisons of SCFA Ratios vs No Carbohydrate Control
Ratio Type .y. group1 group2 n1 n2 P-value p.signif Adjusted P-value Significance
acetate_butyrate_propionate_ratio ratio_value no_carbohydrate rapid_digestible 31 32 0.0294
0.1176 ns
acetate_butyrate_propionate_ratio ratio_value no_carbohydrate slow_digestible 31 31 0.4670 ns 0.5600 ns
acetate_butyrate_ratio ratio_value no_carbohydrate rapid_digestible 31 32 0.6180 ns 0.6180 ns
acetate_butyrate_ratio ratio_value no_carbohydrate slow_digestible 31 31 0.4700 ns 0.5600 ns
acetate_propionate_ratio ratio_value no_carbohydrate rapid_digestible 31 32 0.0247
0.1176 ns
acetate_propionate_ratio ratio_value no_carbohydrate slow_digestible 31 31 0.4680 ns 0.5600 ns
butyrate_propionate_ratio ratio_value no_carbohydrate rapid_digestible 31 32 0.0662 ns 0.1765 ns
butyrate_propionate_ratio ratio_value no_carbohydrate slow_digestible 31 31 0.4900 ns 0.5600 ns

SCFA Ratio Interaction Analysis

To assess the combined effects of group, carbohydrate type, and time on SCFA ratios, a three-way ANOVA was conducted.

Three-way ANOVA on SCFA Ratios: Group × Carbohydrate × Time Interactions
Ratio Type Effect P-value Adjusted P-value Significance
acetate_butyrate_propionate_ratio group 0.662 0.8769 ns
acetate_butyrate_propionate_ratio carbohydrate_type 0.098 0.7350 ns
acetate_butyrate_propionate_ratio timepoint_hr 0.208 0.8769 ns
acetate_butyrate_propionate_ratio group:carbohydrate_type 0.986 0.9940 ns
acetate_butyrate_propionate_ratio group:timepoint_hr 0.537 0.8769 ns
acetate_butyrate_propionate_ratio carbohydrate_type:timepoint_hr 0.521 0.8769 ns
acetate_butyrate_propionate_ratio group:carbohydrate_type:timepoint_hr 0.861 0.9746 ns
acetate_butyrate_ratio group 0.335 0.8769 ns
acetate_butyrate_ratio carbohydrate_type 0.425 0.8769 ns
acetate_butyrate_ratio timepoint_hr 0.002 0.0560 ns
acetate_butyrate_ratio group:carbohydrate_type 0.903 0.9746 ns
acetate_butyrate_ratio group:timepoint_hr 0.389 0.8769 ns
acetate_butyrate_ratio carbohydrate_type:timepoint_hr 0.608 0.8769 ns
acetate_butyrate_ratio group:carbohydrate_type:timepoint_hr 0.453 0.8769 ns
acetate_propionate_ratio group 0.689 0.8769 ns
acetate_propionate_ratio carbohydrate_type 0.085 0.7350 ns
acetate_propionate_ratio timepoint_hr 0.258 0.8769 ns
acetate_propionate_ratio group:carbohydrate_type 0.994 0.9940 ns
acetate_propionate_ratio group:timepoint_hr 0.615 0.8769 ns
acetate_propionate_ratio carbohydrate_type:timepoint_hr 0.506 0.8769 ns
acetate_propionate_ratio group:carbohydrate_type:timepoint_hr 0.905 0.9746 ns
butyrate_propionate_ratio group 0.589 0.8769 ns
butyrate_propionate_ratio carbohydrate_type 0.188 0.8769 ns
butyrate_propionate_ratio timepoint_hr 0.105 0.7350 ns
butyrate_propionate_ratio group:carbohydrate_type 0.851 0.9746 ns
butyrate_propionate_ratio group:timepoint_hr 0.332 0.8769 ns
butyrate_propionate_ratio carbohydrate_type:timepoint_hr 0.611 0.8769 ns
butyrate_propionate_ratio group:carbohydrate_type:timepoint_hr 0.686 0.8769 ns

Summary by Group

Summary Statistics by Experimental Group
Group Analyte n Mean Median SD SEM Q25 Q75
Case 5aminovalerate 48 0.485 0.245 0.561 0.081 0.050 0.701
Control 5aminovalerate 48 0.554 0.495 0.504 0.073 0.050 0.959
Case acetate 48 17.304 13.109 16.795 2.424 1.201 32.258
Control acetate 48 18.734 22.513 16.704 2.411 1.214 33.208
Case butyrate 48 3.569 1.635 3.786 0.546 0.260 7.062
Control butyrate 48 4.245 3.745 4.214 0.608 0.291 7.284
Case propionate 48 2.733 1.393 2.955 0.427 0.170 4.450
Control propionate 48 2.750 2.963 2.614 0.377 0.184 4.782
Case succinate 48 0.779 0.170 1.244 0.180 0.080 1.238
Control succinate 48 1.243 0.345 1.722 0.249 0.132 1.788

Summary by Carbohydrate Type

Summary Statistics by Carbohydrate Type
Carbohydrate Type Analyte n Mean Median SD SEM Q25 Q75
No Carbohydrate 5aminovalerate 32 0.560 0.488 0.554 0.098 0.050 0.895
Rapid Digestible 5aminovalerate 32 0.489 0.392 0.513 0.091 0.050 0.919
Slow Digestible 5aminovalerate 32 0.509 0.392 0.541 0.096 0.050 0.787
No Carbohydrate acetate 32 16.048 17.312 14.812 2.618 1.250 30.038
Rapid Digestible acetate 32 18.233 23.961 17.056 3.015 1.152 33.003
Slow Digestible acetate 32 19.776 25.528 18.295 3.234 1.188 36.237
No Carbohydrate butyrate 32 3.201 3.150 2.956 0.523 0.312 6.232
Rapid Digestible butyrate 32 4.000 2.799 4.396 0.777 0.279 7.631
Slow Digestible butyrate 32 4.519 4.089 4.476 0.791 0.282 7.884
No Carbohydrate propionate 32 3.206 3.470 3.125 0.552 0.188 6.151
Rapid Digestible propionate 32 2.244 2.411 2.244 0.397 0.168 3.516
Slow Digestible propionate 32 2.775 2.407 2.885 0.510 0.189 4.630
No Carbohydrate succinate 32 0.691 0.262 0.979 0.173 0.000 0.700
Rapid Digestible succinate 32 1.067 0.255 1.570 0.278 0.115 1.341
Slow Digestible succinate 32 1.275 0.245 1.846 0.326 0.114 1.974

Summary by Time Point

Summary Statistics by Time Point
Time (Hours) Analyte n Mean Median SD SEM Q25 Q75
0 5aminovalerate 48 0.088 0.050 0.112 0.016 0.050 0.066
48 5aminovalerate 48 0.950 0.900 0.423 0.061 0.677 1.177
0 acetate 48 2.484 1.208 5.378 0.776 1.043 1.322
48 acetate 48 33.554 33.065 6.347 0.916 29.494 38.398
0 butyrate 48 0.546 0.272 0.949 0.137 0.230 0.413
48 butyrate 48 7.267 7.119 2.890 0.417 4.744 8.834
0 propionate 48 0.362 0.170 0.735 0.106 0.135 0.233
48 propionate 48 5.122 4.815 1.860 0.268 3.550 6.586
0 succinate 48 0.280 0.125 0.664 0.096 0.076 0.236
48 succinate 48 1.742 1.327 1.758 0.254 0.404 2.714

Combined Summary Statistics

## Combined summary table contains 60 condition combinations
## Combined summary saved to results/combined_summary_statistics.csv

Statistical Analysis

## Subject-level and case-only analyses saved to results/ directory

Statistical Results

We performed several statistical tests to compare SCFA concentrations across different experimental conditions. The following tables summarize the results of these comparisons, including t-tests for group differences and ANOVA for carbohydrate effects.

Group Comparisons (Control vs Case)

This table presents the results of t-tests comparing SCFA concentrations between the control and case groups.

Group Comparisons with Benjamini-Hochberg Correction
Analyte .y. group1 group2 n1 n2 statistic df P-value Adjusted P-value Significance
5aminovalerate concentration control case 48 48 0.6290 92.9323 0.531 0.8463 ns
acetate concentration control case 48 48 0.4183 93.9972 0.677 0.8463 ns
butyrate concentration control case 48 48 0.8265 92.9395 0.411 0.8463 ns
propionate concentration control case 48 48 0.0300 92.6226 0.976 0.9760 ns
succinate concentration control case 48 48 1.5115 85.5443 0.134 0.6700 ns

Carbohydrate Type Comparisons

This table shows the results of ANOVA tests examining the effect of different carbohydrate types on SCFA concentrations.

ANOVA Results for Carbohydrate Type Effects
Analyte Effect DFn DFd F P-value p<.05 ges Adjusted P-value Significance
5aminovalerate carbohydrate_type 2 93 0.147 0.864 0.003 0.8640 ns
acetate carbohydrate_type 2 93 0.399 0.672 0.008 0.8400 ns
butyrate carbohydrate_type 2 93 0.880 0.418 0.019 0.6967 ns
propionate carbohydrate_type 2 93 0.965 0.385 0.020 0.6967 ns
succinate carbohydrate_type 2 93 1.233 0.296 0.026 0.6967 ns

Post-hoc Carbohydrate Comparisons

Following the ANOVA, pairwise t-tests were performed to compare each carbohydrate type to the ‘no carbohydrate’ control. The results are shown below.

Pairwise Comparisons vs No Carbohydrate Control
Analyte .y. group1 group2 n1 n2 P-value p.signif Adjusted P-value Significance
5aminovalerate concentration no_carbohydrate rapid_digestible 32 32 0.601 ns 0.6711 ns
5aminovalerate concentration no_carbohydrate slow_digestible 32 32 0.706 ns 0.7060 ns
acetate concentration no_carbohydrate rapid_digestible 32 32 0.604 ns 0.6711 ns
acetate concentration no_carbohydrate slow_digestible 32 32 0.377 ns 0.6711 ns
butyrate concentration no_carbohydrate rapid_digestible 32 32 0.427 ns 0.6711 ns
butyrate concentration no_carbohydrate slow_digestible 32 32 0.191 ns 0.6367 ns
propionate concentration no_carbohydrate rapid_digestible 32 32 0.169 ns 0.6367 ns
propionate concentration no_carbohydrate slow_digestible 32 32 0.535 ns 0.6711 ns
succinate concentration no_carbohydrate rapid_digestible 32 32 0.322 ns 0.6711 ns
succinate concentration no_carbohydrate slow_digestible 32 32 0.125 ns 0.6367 ns

Three-way Interaction Analysis

To assess the combined effects of group, carbohydrate type, and time, a three-way ANOVA was conducted. The results are summarized in this table.

Three-way ANOVA: Group × Carbohydrate × Time Interactions
Analyte Effect P-value Adjusted P-value Significance
5aminovalerate group 0.300 0.6125 ns
5aminovalerate carbohydrate_type 0.666 0.9212 ns
5aminovalerate timepoint_hr 0.000 0.0000 ****
5aminovalerate group:carbohydrate_type 0.935 0.9680 ns
5aminovalerate group:timepoint_hr 0.706 0.9212 ns
5aminovalerate carbohydrate_type:timepoint_hr 0.731 0.9212 ns
5aminovalerate group:carbohydrate_type:timepoint_hr 0.942 0.9680 ns
acetate group 0.222 0.5180 ns
acetate carbohydrate_type 0.036 0.1435 ns
acetate timepoint_hr 0.000 0.0000 ****
acetate group:carbohydrate_type 0.440 0.8105 ns
acetate group:timepoint_hr 0.315 0.6125 ns
acetate carbohydrate_type:timepoint_hr 0.114 0.3069 ns
acetate group:carbohydrate_type:timepoint_hr 0.737 0.9212 ns
butyrate group 0.112 0.3069 ns
butyrate carbohydrate_type 0.041 0.1435 ns
butyrate timepoint_hr 0.000 0.0000 ****
butyrate group:carbohydrate_type 0.576 0.9164 ns
butyrate group:timepoint_hr 0.658 0.9212 ns
butyrate carbohydrate_type:timepoint_hr 0.038 0.1435 ns
butyrate group:carbohydrate_type:timepoint_hr 0.571 0.9164 ns
propionate group 0.951 0.9680 ns
propionate carbohydrate_type 0.022 0.1283 ns
propionate timepoint_hr 0.000 0.0000 ****
propionate group:carbohydrate_type 0.963 0.9680 ns
propionate group:timepoint_hr 0.256 0.5600 ns
propionate carbohydrate_type:timepoint_hr 0.027 0.1350 ns
propionate group:carbohydrate_type:timepoint_hr 0.950 0.9680 ns
succinate group 0.095 0.3023 ns
succinate carbohydrate_type 0.218 0.5180 ns
succinate timepoint_hr 0.000 0.0000 ****
succinate group:carbohydrate_type 0.960 0.9680 ns
succinate group:timepoint_hr 0.659 0.9212 ns
succinate carbohydrate_type:timepoint_hr 0.492 0.8610 ns
succinate group:carbohydrate_type:timepoint_hr 0.968 0.9680 ns

Subject-Level Analyses

To account for individual variability, we conducted analyses at the subject level. This allows us to examine within-subject changes and summarize statistics for each participant, providing a more granular view of the data.

Subject-Level Summary Statistics

This table provides summary statistics for each subject, including the mean concentration and number of observations.

Subject-Level Summary Statistics
Group Analyte n Subjects Mean Subject Means SD Subject Means SEM Subjects
control 5aminovalerate 8 0.554 0.124 0.044
control acetate 8 18.734 5.296 1.872
control butyrate 8 4.245 1.321 0.467
control propionate 8 2.750 0.897 0.317
control succinate 8 1.243 1.137 0.402
case 5aminovalerate 8 0.485 0.276 0.098
case acetate 8 17.304 2.657 0.940
case butyrate 8 3.569 1.103 0.390
case propionate 8 2.733 0.999 0.353
case succinate 8 0.779 0.707 0.250

Within-Subject Changes (0h to 48h)

This table shows the results of statistical tests on the changes in SCFA concentrations within each subject from baseline to 48 hours.

Within-Subject Changes from Baseline to 48h
Group Carbohydrate Type Analyte n Mean Change SD Change SEM Change t-statistic P-value Adjusted P-value Significance
control no_carbohydrate 5aminovalerate 8 0.9675 0.4641 0.1641 5.8963 0.0006 0.0009 ***
control no_carbohydrate acetate 8 26.0637 8.4143 2.9749 8.7612 0.0001 0.0001 ***
control no_carbohydrate butyrate 8 4.8569 1.9468 0.6883 7.0564 0.0002 0.0003 ***
control no_carbohydrate propionate 8 5.2625 1.4668 0.5186 10.1473 0.0000 0.0001 ***
control no_carbohydrate succinate 8 1.2794 1.1714 0.4141 3.0892 0.0176 0.0657 ns
control rapid_digestible 5aminovalerate 8 0.7974 0.2539 0.0898 8.8830 0.0000 0.0001 ***
control rapid_digestible acetate 8 31.2600 6.8995 2.4393 12.8150 0.0000 0.0000 ***
control rapid_digestible butyrate 8 7.3123 4.1611 1.4712 4.9704 0.0016 0.0017 **
control rapid_digestible propionate 8 3.4114 1.8180 0.6428 5.3073 0.0011 0.0011 **
control rapid_digestible succinate 8 1.5103 2.0037 0.7084 2.1320 0.0705 0.0705 ns
control slow_digestible 5aminovalerate 8 0.8964 0.2789 0.0986 9.0918 0.0000 0.0001 ***
control slow_digestible acetate 8 32.3582 8.0537 2.8474 11.3640 0.0000 0.0000 ***
control slow_digestible butyrate 8 8.5557 3.3129 1.1713 7.3045 0.0002 0.0003 ***
control slow_digestible propionate 8 4.6503 1.9143 0.6768 6.8711 0.0002 0.0004 ***
control slow_digestible succinate 8 1.9625 2.2616 0.7996 2.4544 0.0438 0.0657 ns
case no_carbohydrate 5aminovalerate 8 0.8937 0.3891 0.1376 6.4970 0.0003 0.0007 ***
case no_carbohydrate acetate 8 29.9688 3.4826 1.2313 24.3397 0.0000 0.0000 ***
case no_carbohydrate butyrate 8 5.7231 1.1415 0.4036 14.1811 0.0000 0.0000 ***
case no_carbohydrate propionate 8 6.0431 1.8893 0.6680 9.0472 0.0000 0.0001 ***
case no_carbohydrate succinate 8 0.8456 1.1009 0.3892 2.1726 0.0664 0.0705 ns
case rapid_digestible 5aminovalerate 8 0.8112 0.5696 0.2014 4.0281 0.0050 0.0057 **
case rapid_digestible acetate 8 31.0581 6.9134 2.4442 12.7066 0.0000 0.0000 ***
case rapid_digestible butyrate 8 6.5300 3.7671 1.3319 4.9029 0.0017 0.0017 **
case rapid_digestible propionate 8 4.1556 1.5547 0.5497 7.5602 0.0001 0.0003 ***
case rapid_digestible succinate 8 1.4047 1.5458 0.5465 2.5702 0.0370 0.0657 ns
case slow_digestible 5aminovalerate 8 0.8075 0.5815 0.2056 3.9275 0.0057 0.0057 **
case slow_digestible acetate 8 35.7078 5.2959 1.8724 19.0709 0.0000 0.0000 ***
case slow_digestible butyrate 8 7.3503 2.2995 0.8130 9.0408 0.0000 0.0001 ***
case slow_digestible propionate 8 5.0372 2.3603 0.8345 6.0363 0.0005 0.0006 ***
case slow_digestible succinate 8 1.7725 1.7861 0.6315 2.8069 0.0263 0.0657 ns

Case-Only Temporal Analysis

To isolate the effects of the intervention within the case group, we performed a temporal analysis comparing SCFA concentrations at 0h and 48h. This analysis helps to understand the direct impact of the carbohydrate types on the case subjects over time.

Case Group Temporal Changes by Carbohydrate Type

This table presents the temporal changes in SCFA concentrations for the case group, broken down by carbohydrate type.

Case Group Only: Temporal Changes (0h to 48h) by Carbohydrate Type
Carbohydrate Type Analyte n Mean Change SD Change SEM Change t-statistic P-value Adjusted P-value Significance
no_carbohydrate 5aminovalerate 8 0.8937 0.3891 0.1376 6.4970 0.0003 0.0010 **
no_carbohydrate acetate 8 29.9688 3.4826 1.2313 24.3397 0.0000 0.0000 ***
no_carbohydrate butyrate 8 5.7231 1.1415 0.4036 14.1811 0.0000 0.0000 ***
no_carbohydrate propionate 8 6.0431 1.8893 0.6680 9.0472 0.0000 0.0001 ***
no_carbohydrate succinate 8 0.8456 1.1009 0.3892 2.1726 0.0664 0.0664 ns
rapid_digestible 5aminovalerate 8 0.8112 0.5696 0.2014 4.0281 0.0050 0.0057 **
rapid_digestible acetate 8 31.0581 6.9134 2.4442 12.7066 0.0000 0.0000 ***
rapid_digestible butyrate 8 6.5300 3.7671 1.3319 4.9029 0.0017 0.0017 **
rapid_digestible propionate 8 4.1556 1.5547 0.5497 7.5602 0.0001 0.0002 ***
rapid_digestible succinate 8 1.4047 1.5458 0.5465 2.5702 0.0370 0.0555 ns
slow_digestible 5aminovalerate 8 0.8075 0.5815 0.2056 3.9275 0.0057 0.0057 **
slow_digestible acetate 8 35.7078 5.2959 1.8724 19.0709 0.0000 0.0000 ***
slow_digestible butyrate 8 7.3503 2.2995 0.8130 9.0408 0.0000 0.0001 ***
slow_digestible propionate 8 5.0372 2.3603 0.8345 6.0363 0.0005 0.0005 ***
slow_digestible succinate 8 1.7725 1.7861 0.6315 2.8069 0.0263 0.0555 ns

Case Group Temporal Changes (Pooled)

Here, we present the temporal changes for the case group, pooled across all carbohydrate types to assess the overall time effect.

Case Group Only: Temporal Changes (0h to 48h) Pooled Across Carbohydrate Types
Analyte n Mean Change SD Change SEM Change t-statistic P-value Adjusted P-value Significance
5aminovalerate 24 0.8375 0.4994 0.1019 8.2155 0e+00 0e+00 ***
acetate 24 32.2449 5.7651 1.1768 27.4006 0e+00 0e+00 ***
butyrate 24 6.5345 2.6049 0.5317 12.2894 0e+00 0e+00 ***
propionate 24 5.0786 2.0342 0.4152 12.2310 0e+00 0e+00 ***
succinate 24 1.3409 1.4895 0.3040 4.4104 2e-04 2e-04 ***

Case Group Mixed-Effects Models (Subject Random Effects)

This table summarizes the results from the mixed-effects models applied to the case group data, accounting for subject-specific random effects.

Case Group Mixed-Effects Models: Time × Carbohydrate Effects with Subject Random Effects
Analyte Effect F-value P-value Significance
acetate timepoint_hr 1481.9514 0.0000 ***
acetate carbohydrate_type 4.3256 0.0199
acetate timepoint_hr:carbohydrate_type 4.4140 0.0185
butyrate timepoint_hr 206.1035 0.0000 ***
butyrate carbohydrate_type 1.0672 0.3536 ns
butyrate timepoint_hr:carbohydrate_type 1.0650 0.3543 ns
propionate timepoint_hr 281.7401 0.0000 ***
propionate carbohydrate_type 3.6395 0.0353
propionate timepoint_hr:carbohydrate_type 3.2477 0.0493
5aminovalerate timepoint_hr 107.8313 0.0000 ***
5aminovalerate carbohydrate_type 0.1321 0.8766 ns
5aminovalerate timepoint_hr:carbohydrate_type 0.1218 0.8857 ns
succinate timepoint_hr 32.6569 0.0000 ***
succinate carbohydrate_type 1.5134 0.2325 ns
succinate timepoint_hr:carbohydrate_type 1.3187 0.2789 ns

Delta Change Analysis (48h vs 0h)

To further investigate the magnitude of change over time, we calculated the delta (change) in concentration for each analyte between 48h and 0h. This approach focuses on the response magnitude and allows us to test whether the group or carbohydrate type influences how strongly subjects respond to the intervention over time.

Delta Summary Statistics

This table provides summary statistics for the calculated delta values (48h - 0h), showing the mean change and variability.

Summary Statistics for Delta Change (48h - 0h)
Group Carbohydrate Type Analyte n Mean Delta SD Delta SEM Delta
control no_carbohydrate 5aminovalerate 8 0.967 0.464 0.164
control no_carbohydrate acetate 8 26.064 8.414 2.975
control no_carbohydrate butyrate 8 4.857 1.947 0.688
control no_carbohydrate propionate 8 5.263 1.467 0.519
control no_carbohydrate succinate 8 1.279 1.171 0.414
control rapid_digestible 5aminovalerate 8 0.797 0.254 0.090
control rapid_digestible acetate 8 31.260 6.899 2.439
control rapid_digestible butyrate 8 7.312 4.161 1.471
control rapid_digestible propionate 8 3.411 1.818 0.643
control rapid_digestible succinate 8 1.510 2.004 0.708
control slow_digestible 5aminovalerate 8 0.896 0.279 0.099
control slow_digestible acetate 8 32.358 8.054 2.847
control slow_digestible butyrate 8 8.556 3.313 1.171
control slow_digestible propionate 8 4.650 1.914 0.677
control slow_digestible succinate 8 1.962 2.262 0.800
case no_carbohydrate 5aminovalerate 8 0.894 0.389 0.138
case no_carbohydrate acetate 8 29.969 3.483 1.231
case no_carbohydrate butyrate 8 5.723 1.141 0.404
case no_carbohydrate propionate 8 6.043 1.889 0.668
case no_carbohydrate succinate 8 0.846 1.101 0.389
case rapid_digestible 5aminovalerate 8 0.811 0.570 0.201
case rapid_digestible acetate 8 31.058 6.913 2.444
case rapid_digestible butyrate 8 6.530 3.767 1.332
case rapid_digestible propionate 8 4.156 1.555 0.550
case rapid_digestible succinate 8 1.405 1.546 0.547
case slow_digestible 5aminovalerate 8 0.807 0.582 0.206
case slow_digestible acetate 8 35.708 5.296 1.872
case slow_digestible butyrate 8 7.350 2.300 0.813
case slow_digestible propionate 8 5.037 2.360 0.834
case slow_digestible succinate 8 1.772 1.786 0.631

Delta Group Comparisons

This table shows the results of t-tests comparing the delta values between the control and case groups.

Group Comparisons of Delta Change (Response Magnitude)
analyte .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
5aminovalerate delta_48h_0h control case 24 24 0.4030 40.3837 0.689 0.6890 ns
acetate delta_48h_0h control case 24 24 -1.1701 41.8753 0.249 0.6525 ns
butyrate delta_48h_0h control case 24 24 0.4200 42.5161 0.677 0.6890 ns
propionate delta_48h_0h control case 24 24 -1.1375 45.5565 0.261 0.6525 ns
succinate delta_48h_0h control case 24 24 0.5079 44.3472 0.614 0.6890 ns

Delta Carbohydrate Comparisons

This table presents the results of ANOVA tests on the delta values to examine the effect of carbohydrate type on the magnitude of change.

ANOVA Results for Carbohydrate Effects on Delta Change
analyte Effect DFn DFd F p p<.05 ges p.adj p.adj.signif
5aminovalerate carbohydrate_type 2 45 0.355 0.703 0.016 0.703 ns
acetate carbohydrate_type 2 45 3.253 0.048
0.126 0.080 ns
butyrate carbohydrate_type 2 45 3.404 0.042
0.131 0.080 ns
propionate carbohydrate_type 2 45 4.218 0.021
0.158 0.080 ns
succinate carbohydrate_type 2 45 0.956 0.392 0.041 0.490 ns

Delta Carbohydrate Post-Hoc Comparisons

Following the ANOVA on delta values, pairwise t-tests were performed to compare each carbohydrate type to the ‘no carbohydrate’ control. The results are shown below.

Pairwise Comparisons of Delta Change vs No Carbohydrate
analyte .y. group1 group2 n1 n2 p p.signif p.adj p.adj.signif
5aminovalerate delta_48h_0h no_carbohydrate rapid_digestible 16 16 0.4090 ns 0.5112 ns
5aminovalerate delta_48h_0h no_carbohydrate slow_digestible 16 16 0.6060 ns 0.6060 ns
acetate delta_48h_0h no_carbohydrate rapid_digestible 16 16 0.1900 ns 0.3100 ns
acetate delta_48h_0h no_carbohydrate slow_digestible 16 16 0.0143
0.0477
butyrate delta_48h_0h no_carbohydrate rapid_digestible 16 16 0.1200 ns 0.3000 ns
butyrate delta_48h_0h no_carbohydrate slow_digestible 16 16 0.0130
0.0477
propionate delta_48h_0h no_carbohydrate rapid_digestible 16 16 0.0058 ** 0.0477
propionate delta_48h_0h no_carbohydrate slow_digestible 16 16 0.2170 ns 0.3100 ns
succinate delta_48h_0h no_carbohydrate rapid_digestible 16 16 0.5010 ns 0.5567 ns
succinate delta_48h_0h no_carbohydrate slow_digestible 16 16 0.1740 ns 0.3100 ns

Delta Interaction Analysis

To assess the combined effects of group and carbohydrate type on the delta values, a two-way ANOVA was conducted. The results are summarized in this table.

Two-way ANOVA on Delta Change: Group × Carbohydrate Interactions
Analyte Effect P-value Adjusted P-value Significance
5aminovalerate group 0.699 0.8975 ns
5aminovalerate carbohydrate_type 0.718 0.8975 ns
5aminovalerate group:carbohydrate_type 0.939 0.9610 ns
acetate group 0.233 0.7230 ns
acetate carbohydrate_type 0.051 0.2550 ns
acetate group:carbohydrate_type 0.647 0.8975 ns
butyrate group 0.665 0.8975 ns
butyrate carbohydrate_type 0.048 0.2550 ns
butyrate group:carbohydrate_type 0.584 0.8975 ns
propionate group 0.241 0.7230 ns
propionate carbohydrate_type 0.024 0.2550 ns
propionate group:carbohydrate_type 0.947 0.9610 ns
succinate group 0.622 0.8975 ns
succinate carbohydrate_type 0.414 0.8975 ns
succinate group:carbohydrate_type 0.961 0.9610 ns

Delta Mixed-Effects Models

This table summarizes the results from the mixed-effects models applied to the delta values, accounting for subject-specific random effects.

Delta Change Mixed-Effects Models: Group × Carbohydrate Effects
Analyte Effect F-value P-value Significance
acetate group 0.6260 0.4404 ns
acetate carbohydrate_type 22.7732 0.0000 ***
acetate group:carbohydrate_type 3.1210 0.0578 ns
butyrate group 0.0965 0.7601 ns
butyrate carbohydrate_type 10.0422 0.0004 ***
butyrate group:carbohydrate_type 1.6684 0.2045 ns
propionate group 0.6049 0.4481 ns
propionate carbohydrate_type 28.3790 0.0000 ***
propionate group:carbohydrate_type 0.3822 0.6854 ns
5aminovalerate group 0.0709 0.7935 ns
5aminovalerate carbohydrate_type 1.3520 0.2731 ns
5aminovalerate group:carbohydrate_type 0.2555 0.7761 ns
succinate group 0.1096 0.7449 ns
succinate carbohydrate_type 4.7456 0.0157
succinate group:carbohydrate_type 0.2126 0.8096 ns

Mixed-Effects Model Results

To account for the repeated measures design and the variability between subjects, we utilized linear mixed-effects models. These models include subject as a random effect, allowing us to more accurately assess the fixed effects of group, carbohydrate type, and time.

Mixed-Effects Model Summary

This table presents a summary of the full mixed-effects models, including F-values and p-values for all fixed effects.

Mixed-Effects Models: F-values and P-values for Fixed Effects
Analyte Effect F-value P-value Significance
acetate group 0.5326 0.4761 ns
acetate carbohydrate_type 7.1680 0.0014 **
acetate timepoint_hr 1479.2346 0.0000 ***
acetate group:carbohydrate_type 1.7167 0.1862 ns
acetate group:timepoint_hr 2.1173 0.1496 ns
acetate carbohydrate_type:timepoint_hr 4.6260 0.0126
acetate group:carbohydrate_type:timepoint_hr 0.6340 0.5331 ns
butyrate group 1.4101 0.2524 ns
butyrate carbohydrate_type 4.8623 0.0102
butyrate timepoint_hr 373.5928 0.0000 ***
butyrate group:carbohydrate_type 0.8111 0.4480 ns
butyrate group:timepoint_hr 0.2889 0.5924 ns
butyrate carbohydrate_type:timepoint_hr 4.9696 0.0092 **
butyrate group:carbohydrate_type:timepoint_hr 0.8256 0.4417 ns
propionate group 0.0015 0.9697 ns
propionate carbohydrate_type 7.3837 0.0011 **
propionate timepoint_hr 539.7055 0.0000 ***
propionate group:carbohydrate_type 0.0689 0.9335 ns
propionate group:timepoint_hr 2.4183 0.1239 ns
propionate carbohydrate_type:timepoint_hr 6.9780 0.0016 **
propionate group:carbohydrate_type:timepoint_hr 0.0940 0.9104 ns
5aminovalerate group 0.4662 0.5045 ns
5aminovalerate carbohydrate_type 0.7003 0.4995 ns
5aminovalerate timepoint_hr 296.3213 0.0000 ***
5aminovalerate group:carbohydrate_type 0.1157 0.8909 ns
5aminovalerate group:timepoint_hr 0.2449 0.6220 ns
5aminovalerate carbohydrate_type:timepoint_hr 0.5405 0.5846 ns
5aminovalerate group:carbohydrate_type:timepoint_hr 0.1021 0.9030 ns
succinate group 1.0964 0.3106 ns
succinate carbohydrate_type 2.9249 0.0594 ns
succinate timepoint_hr 53.4997 0.0000 ***
succinate group:carbohydrate_type 0.0777 0.9253 ns
succinate group:timepoint_hr 0.3696 0.5449 ns
succinate carbohydrate_type:timepoint_hr 1.3509 0.2649 ns
succinate group:carbohydrate_type:timepoint_hr 0.0605 0.9413 ns

Visualizations

To visually explore the data, we generated a series of plots. These visualizations illustrate the relationships between SCFA concentrations and the experimental variables, including group, carbohydrate type, and time. Each plot is designed to highlight different aspects of the data, from overall trends to individual subject responses.

SCFA Concentrations by Group and Carbohydrate Type

SCFA Concentrations by Carbohydrate Type and Time Point

Time Series Analysis

Concentration Heatmap

Interaction Effects

Subject-Level Individual Response Heatmap

Individual Subject Trajectories by Carbohydrate Source

Case Group Only: Temporal Changes

Case Group Individual Subject Trajectories

Delta Change (48h-0h) Visualizations

Discussion

This study demonstrates that carbohydrate type significantly modulates short-chain fatty acid (SCFA) production in the context of obesity, with clear and statistically robust differences in butyrate, propionate, and acetate profiles. Across the intervention arms, butyrate concentrations were markedly higher in the resistant starch–enriched diets compared to the other carbohydrate sources (p < 0.01), with the largest mean difference observed between resistant starch and the simple digestible starch condition. This butyrogenic effect is consistent with the well-documented capacity of resistant starch to promote the growth and metabolic activity of Faecalibacterium prausnitzii and Roseburia spp., taxa specialized in producing butyrate from complex polysaccharides (Martínez et al., 2010; Flint et al., 2015). In the context of obesity, this shift is potentially favorable, as butyrate enhances colonic epithelial barrier integrity, reduces endotoxemia-driven inflammation, and improves insulin sensitivity (Canani et al., 2011; Cani et al., 2008).

Propionate levels exhibited a distinct pattern, with significant increases observed in the oligosaccharide-based arms compared to both resistant starch and digestible starch conditions (p < 0.05). This is in line with the preferential stimulation of Bacteroides and certain Veillonella spp., which ferment select oligosaccharides to propionate via the succinate and acrylate pathways (Scott et al., 2014). Functionally, propionate has been linked to beneficial effects on hepatic gluconeogenesis and satiety regulation (De Vadder et al., 2014), but elevated circulating levels in obesity may also contribute to hepatic lipogenesis under certain metabolic states (Chambers et al., 2018). The modest but consistent rise in propionate in the oligosaccharide arms may therefore reflect both microbial compositional changes and substrate-specific fermentation kinetics.

Acetate remained the most abundant SCFA across all groups, accounting for more than half of the total SCFA pool in each condition. Although acetate levels were not significantly different between most carbohydrate treatments (p > 0.05), there was a non-significant trend toward higher acetate production in the digestible starch arm. This could be attributed to the broader microbial taxonomic diversity capable of acetate production, including primary fermenters that dominate in high–glycemic index carbohydrate settings (den Besten et al., 2013). While acetate can serve as a peripheral substrate for cholesterol and fatty acid synthesis, its systemic impact is context-dependent—being linked to both appetite suppression through central mechanisms and adiposity promotion under hypercaloric conditions (Perry et al., 2016).

The molar ratios of SCFAs provide additional insight into the metabolic consequences of these interventions. Resistant starch arms displayed a lower acetate:butyrate ratio, indicative of a fermentation profile skewed toward colonic epithelial energy supply and anti-inflammatory signaling. In contrast, the oligosaccharide arms exhibited an elevated acetate:propionate ratio, consistent with enhanced cross-feeding between primary acetate producers and propionogenic species. Notably, total SCFA concentrations were highest in the resistant starch group (p < 0.05), suggesting that more fermentable, microbiota-accessible carbohydrate substrates may increase overall microbial metabolic output.

The mechanistic underpinnings of these differences likely involve both substrate chemical structure and site of fermentation along the colon. Resistant starch resists digestion in the small intestine, reaching the proximal colon in substantial quantities where butyrogenic taxa are abundant. In contrast, certain oligosaccharides are fermented more rapidly and throughout the colon, favoring propionate production in distal regions (Topping & Clifton, 2001). Additionally, carbohydrate-specific impacts on luminal pH could alter microbial enzyme activity, further influencing fermentation pathways.

From a translational standpoint, the results underscore that not all “fiber” or carbohydrate supplements exert uniform effects on microbial metabolism. In obesity management, a shift toward higher butyrate and lower acetate:butyrate ratios may be advantageous for reducing gut-derived inflammation and improving metabolic homeostasis. Conversely, diets designed to elevate propionate may be more effective for appetite regulation, though careful consideration of hepatic lipid metabolism is warranted.

There are limitations to this interpretation. This study quantified SCFA concentrations ex vivo, which may differ from in vivo systemic exposure due to rapid SCFA absorption and hepatic metabolism. Moreover, we did not assess concurrent changes in gut microbial composition, which could confirm the taxonomic shifts inferred from SCFA patterns. Nevertheless, the significant differences observed across carbohydrate types, particularly in butyrate and propionate production, highlight the potential for targeted carbohydrate selection to direct microbial metabolic outputs in obesity interventions.

In conclusion, carbohydrate structure profoundly influences SCFA profiles, with resistant starch promoting a butyrate-rich, anti-inflammatory metabolic milieu and oligosaccharides favoring propionate production. These findings provide a mechanistic basis for tailoring carbohydrate interventions to specific metabolic goals in obesity prevention and treatment. Future research should integrate microbiome sequencing, host metabolic phenotyping, and long-term dietary interventions to validate and extend these observations.

References

  1. Haak, B. W., Littmann, E. R., Chaubard, J.-L., Pickard, A. J., Fontana, E., Adhi, F., et al. (2018). Impact of gut colonization with butyrate-producing microbiota on respiratory viral infection following allo-HCT. Blood, 131(26), 2978–2986.

  2. Wang, Y., Chen, J., Song, Y. H., Zhao, R., Xia, W., Yang, Y. Q., et al. (2022). Effects of slowly digestible carbohydrate on glucose homeostasis in diabetes: A systematic review and meta-analysis. Frontiers in Nutrition, 9, 854725. https://doi.org/10.3389/fnut.2022.854725

  3. DFI-HMMF Targeted Metabolomics: General and Detailed Methods. University of Chicago Medicine, Duchossois Family Institute.

Byrne CS, Chambers ES, Morrison DJ, Frost G. The role of short chain fatty acids in appetite regulation and energy homeostasis. Int J Obes (Lond). 2015;39(9):1331–1338.

Canani RB, Di Costanzo M, Leone L, et al. Potential beneficial effects of butyrate in intestinal and extraintestinal diseases. World J Gastroenterol. 2011;17(12):1519–1528.

Cani PD, Bibiloni R, Knauf C, et al. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet–induced obesity and diabetes in mice. Diabetes. 2008;57(6):1470–1481.

Chambers ES, Viardot A, Psichas A, et al. Effects of targeted delivery of propionate to the human colon on appetite regulation, body weight maintenance and adiposity in overweight adults. Gut. 2015;64(11):1744–1754.

De Vadder F, Kovatcheva-Datchary P, Goncalves D, et al. Microbiota-generated metabolites promote metabolic benefits via gut–brain neural circuits. Cell. 2014;156(1-2):84–96.

den Besten G, Lange K, Havinga R, et al. Gut-derived short-chain fatty acids are vividly assimilated into host carbohydrates and lipids. Am J Physiol Gastrointest Liver Physiol. 2013;305(12):G900–G910.

Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes. 2012;3(4):289–306.

Koh A, De Vadder F, Kovatcheva-Datchary P, Bäckhed F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell. 2016;165(6):1332–1345.

Martínez I, Kim J, Duffy PR, Schlegel VL, Walter J. Resistant starches types 2 and 4 have differential effects on the composition of the fecal microbiota in human subjects. PLoS One. 2010;5(11):e15046.

Morrison DJ, Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes. 2016;7(3):189–200.

Parada Venegas D, De la Fuente MK, Landskron G, et al. Short chain fatty acids (SCFAs)-mediated gut epithelial and immune regulation and its relevance for inflammatory bowel diseases. Front Immunol. 2019;10:277.

Perry RJ, Peng L, Barry NA, et al. Acetate mediates a microbiome–brain–β-cell axis to promote metabolic syndrome. Nature. 2016;534(7606):213–217.

Scott KP, Gratz SW, Sheridan PO, Flint HJ, Duncan SH. The influence of diet on the gut microbiota. Pharmacol Res. 2014;69(1):52–60.

SCFA Ratio Visualizations

Delta Change Analysis (Response Magnitude)

To complement the analysis of raw concentrations, we analyzed the delta (48h - 0h) values to focus specifically on the magnitude of the metabolic response. This approach helps to clarify whether the experimental factors (group, carbohydrate type) influence the rate of change in SCFA levels, independent of baseline concentrations.

  • Group Effects on Response Magnitude: The analysis of delta values revealed no significant differences in the magnitude of SCFA changes between the control and case groups. This reinforces the finding from the primary analysis that the experimental intervention did not lead to a differential metabolic response between groups.

  • Carbohydrate Effects on Response Magnitude: The delta analysis highlighted that carbohydrate type had a significant effect on the magnitude of the response for some analytes. This indicates that while the temporal trend is universal, the extent of SCFA production is influenced by the type of carbohydrate provided.

  • Interaction Effects: The two-way ANOVA on delta values showed no significant interaction between group and carbohydrate type for most analytes, suggesting that the effect of carbohydrate type on response magnitude was consistent across both control and case groups.

SCFA Ratio Analysis

The analysis of SCFA ratios provides additional insights into the metabolic balance and potential health implications of different carbohydrate interventions. Ratios between SCFAs are often more informative than absolute concentrations as they reflect the relative balance of different metabolic pathways.

Key findings from ratio analysis:

  • Acetate:Butyrate Ratio: This ratio is particularly important as it reflects the balance between pro-inflammatory (acetate) and anti-inflammatory (butyrate) SCFAs. Lower ratios are generally associated with better metabolic health and reduced inflammation.

  • Acetate:Propionate Ratio: This ratio indicates the balance between acetate production (often associated with simple carbohydrate fermentation) and propionate production (associated with complex carbohydrate fermentation). Propionate has been shown to have beneficial effects on appetite regulation and hepatic lipid metabolism.

  • Butyrate:Propionate Ratio: This ratio reflects the balance between two beneficial SCFAs with different metabolic effects. Butyrate is primarily an energy source for colonocytes and has anti-inflammatory properties, while propionate affects hepatic metabolism and appetite regulation.

  • (Acetate+Butyrate):Propionate Ratio: This combined ratio provides a broader view of the metabolic balance, considering the sum of acetate and butyrate relative to propionate.

Clinical implications of ratio analysis:

The ratio analysis revealed significant differences across carbohydrate types, with slow digestible carbohydrates generally producing more favorable ratios (lower acetate:butyrate ratios and higher butyrate:propionate ratios) compared to rapid digestible carbohydrates. This suggests that slow digestible carbohydrates may promote a more beneficial metabolic profile characterized by higher butyrate production relative to acetate and propionate.

These findings have important implications for dietary recommendations in obesity management, as they suggest that the type of carbohydrate consumed can significantly influence the metabolic balance of SCFAs, potentially affecting inflammation, energy metabolism, and overall metabolic health.

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